关键词: 矩阵分解, 潜在因子模型, 推荐算法, 带冲量的批量学习算法, 混合学习算法

Abstract: In the field of recommendation system, the Recommendation Algorithms（RA） based on matrix factorization is one of research hotspots. To improve the problem, this paper focuses on the algorithm improvement of Latent Factor Model（LFM） in the matrix factorization based RA algorithms. Two basic algorithms are modified to provide more accurate outcomes. Finally, a numerical example, which is used to carry out comparative study among different algorithms, proves that the improved algorithm is better than previous works.

Key words: matrix factorization, Latent Factor Model（LFM）, recommendation algorithm, batch learning algorithm with momentum, mixed learning algorithm